mybib.bib

# Feel free to delete these first few references, which are specific to the template:

@book{hume48,
  author    = "David Hume",
  year      = "1748",
  title     = "An enquiry concerning human understanding",
  address   = "Indianapolis, IN",
  publisher = "Hackett",
  doi       = {https://doi.org/10.1017/CBO9780511808432},
}

@article{Atr03,
  author  = "P Atreides",
  year    = "2003",
  title   = "How to catch a sandworm",
  journal = "Transactions on Terraforming",
  volume  = 21,
  issue   = 3,
  pages   = {261-300}
}

@misc{terradesert,
  author  = {{TerraDesert Team}},
  title   = {Code for terraforming a desert},
  year    = {2000},
  url     = {https://terradesert.com/code/},
  note    = {Accessed 1 Jan. 2000}
}

# These references may be helpful:

@inproceedings{jupyter,
  abstract  = {It is increasingly necessary for researchers in all fields to write computer code, and in order to reproduce research results, it is important that this code is published. We present Jupyter notebooks, a document format for publishing code, results and explanations in a form that is both readable and executable. We discuss various tools and use cases for notebook documents.},
  author    = {Kluyver, Thomas and Ragan-Kelley, Benjamin and Pérez, Fernando and Granger, Brian and Bussonnier, Matthias and Frederic, Jonathan and Kelley, Kyle and Hamrick, Jessica and Grout, Jason and Corlay, Sylvain and Ivanov, Paul and Avila, Damián and Abdalla, Safia and Willing, Carol and {Jupyter development team}},
  editor    = {Loizides, Fernando and Scmidt, Birgit},
  location  = {Netherlands},
  publisher = {IOS Press},
  url       = {https://eprints.soton.ac.uk/403913/},
  booktitle = {Positioning and Power in Academic Publishing: Players, Agents and Agendas},
  year      = {2016},
  pages     = {87--90},
  title     = {Jupyter Notebooks - a publishing format for reproducible computational workflows},
}

@article{matplotlib,
  abstract     = {Matplotlib is a 2D graphics package used for Python for application development, interactive scripting, and publication-quality image generation across user interfaces and operating systems.},
  author       = {Hunter, J. D.},
  publisher    = {IEEE COMPUTER SOC},
  year         = {2007},
	doi          = {https://doi.org/10.1109/MCSE.2007.55},
  journal      = {Computing in Science \& Engineering},
  number       = {3},
  pages        = {90--95},
  title        = {Matplotlib: A 2D graphics environment},
  volume       = {9},
}

@article{numpy,
  author       = {Harris, Charles R. and Millman, K. Jarrod and van der Walt, Stéfan J. and Gommers, Ralf and Virtanen, Pauli and Cournapeau, David and Wieser, Eric and Taylor, Julian and Berg, Sebastian and Smith, Nathaniel J. and Kern, Robert and Picus, Matti and Hoyer, Stephan and van Kerkwijk, Marten H. and Brett, Matthew and Haldane, Allan and del Río, Jaime Fernández and Wiebe, Mark and Peterson, Pearu and Gérard-Marchant, Pierre and Sheppard, Kevin and Reddy, Tyler and Weckesser, Warren and Abbasi, Hameer and Gohlke, Christoph and Oliphant, Travis E.},
  publisher    = {Springer Science and Business Media {LLC}},
  doi          = {https://doi.org/10.1038/s41586-020-2649-2},
  date         = {2020-09},
  year         = {2020},
  journal      = {Nature},
  number       = {7825},
  pages        = {357--362},
  title        = {Array programming with {NumPy}},
  volume       = {585},
}

@misc{pandas1,
  author    = {{The Pandas Development Team}},
  title     = {pandas-dev/pandas: Pandas},
  month     = feb,
  year      = {2020},
  publisher = {Zenodo},
  version   = {latest},
  url       = {https://doi.org/10.5281/zenodo.3509134},
}

@inproceedings{pandas2,
  author    = {Wes McKinney},
  title     = {{D}ata {S}tructures for {S}tatistical {C}omputing in {P}ython},
  booktitle = {{P}roceedings of the 9th {P}ython in {S}cience {C}onference},
  pages     = {56 - 61},
  year      = {2010},
  editor    = {{S}t\'efan van der {W}alt and {J}arrod {M}illman},
	doi       = {https://doi.org/10.25080/Majora-92bf1922-00a},
}

@article{scipy,
  author  = {Virtanen, Pauli and Gommers, Ralf and Oliphant, Travis E. and
            Haberland, Matt and Reddy, Tyler and Cournapeau, David and
            Burovski, Evgeni and Peterson, Pearu and Weckesser, Warren and
            Bright, Jonathan and {van der Walt}, St{\'e}fan J. and
            Brett, Matthew and Wilson, Joshua and Millman, K. Jarrod and
            Mayorov, Nikolay and Nelson, Andrew R. J. and Jones, Eric and
            Kern, Robert and Larson, Eric and Carey, C J and
            Polat, {\.I}lhan and Feng, Yu and Moore, Eric W. and
            {VanderPlas}, Jake and Laxalde, Denis and Perktold, Josef and
            Cimrman, Robert and Henriksen, Ian and Quintero, E. A. and
            Harris, Charles R. and Archibald, Anne M. and
            Ribeiro, Ant{\^o}nio H. and Pedregosa, Fabian and
            {van Mulbregt}, Paul and {SciPy 1.0 Contributors}},
  title   = {{{SciPy} 1.0: Fundamental Algorithms for Scientific
            Computing in Python}},
  journal = {Nature Methods},
  year    = {2020},
  volume  = {17},
  pages   = {261--272},
  adsurl  = {https://rdcu.be/b08Wh},
	doi     = {https://doi.org/10.1038/s41592-019-0686-2},
}

@article{sklearn1,
  author       = {Pedregosa, F. and Varoquaux, G. and Gramfort, A. and Michel, V. and Thirion, B. and Grisel, O. and Blondel, M. and Prettenhofer, P. and Weiss, R. and Dubourg, V. and Vanderplas, J. and Passos, A. and Cournapeau, D. and Brucher, M. and Perrot, M. and Duchesnay, E.},
  year         = {2011},
  journal      = {Journal of Machine Learning Research},
  pages        = {2825--2830},
  title        = {Scikit-learn: Machine Learning in {P}ython},
  volume       = {12},
}

@inproceedings{sklearn2,
  author    = {Buitinck, Lars and Louppe, Gilles and Blondel, Mathieu and Pedregosa, Fabian and Mueller, Andreas and Grisel, Olivier and Niculae, Vlad and Prettenhofer, Peter and Gramfort, Alexandre and Grobler, Jaques and Layton, Robert and VanderPlas, Jake and Joly, Arnaud and Holt, Brian and Varoquaux, Gaël},
  booktitle = {ECML PKDD Workshop: Languages for Data Mining and Machine Learning},
  year      = {2013},
  pages     = {108--122},
  title     = {{API} design for machine learning software: experiences from the scikit-learn project},
}